Video semantic segmentation for robotics is widely used in different applications such as autonomous driving [1]}[2]}, and robot manipulation [3]}[4]}. Object segmentation can aid in grasping, manipulating objects, and learning object affordances [3]}. In robot manipulation, learning to segment new objects incrementally, has significant importance. Real world environments have far more objects and more appearance variation than can be feasibly trained a-priori. Current large-scale datasets such as Image-Net [6]} do not cover this.
